{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 第四章 完善统计图形\n",
    "- 图例和标题；\n",
    "- 刻度的处理；\n",
    "- 添加相应的表格。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 调整图例和标题。\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.arange(0,2.1,.1)\n",
    "y = np.power(x,3)\n",
    "y1 = np.power(x,2)\n",
    "y2 = np.power(x,1)\n",
    "\n",
    "plt.plot(x,y,label = \"$x^3$\",lw= 2)\n",
    "plt.plot(x,y1,label = \"$x^2$\",lw=2)\n",
    "plt.plot(x,y2,label = \"$x^1$\",lw=2)\n",
    "\n",
    "plt.legend(\n",
    "    loc = 'upper left',\n",
    "    #设置图例的具体位置。以原点为（0，0）。而且以图例的左上角为标准。\n",
    "    bbox_to_anchor = (0.03,0.95),\n",
    "    title = \"power function\",\n",
    "    fancybox = True,\n",
    "    shadow = True,\n",
    "    ncol = 3,\n",
    ")\n",
    "plt.title(\"center demo\")\n",
    "plt.title('left demo',\n",
    "          loc = 'left',\n",
    "          fontdict={\"size\":'xx-large',\n",
    "                    'color':'r',\n",
    "                    'family':'Times New Roman'})\n",
    "plt.title('right demo',\n",
    "          loc = 'right',\n",
    "          fontdict={'size':15,\n",
    "                    'color':'blue',\n",
    "                    'family':\"Consolas\"})\n",
    "plt.box(on=True)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,2*np.pi)\n",
    "y = np.sin(x)\n",
    "plt.plot(x,y,lw = 2, c = 'blue',)\n",
    "plt.axhline(0,c = 'k',ls = ':')\n",
    "plt.axhline(1,xmin=0, xmax = np.pi/12, c = 'k',ls = ':')\n",
    "key_dots = [0,np.pi/2,np.pi,np.pi*3/2,2*np.pi]\n",
    "plt.scatter(key_dots,np.sin(key_dots), c = 'k',lw = .5,alpha=.7)\n",
    "\n",
    "plt.xticks(key_dots ,\n",
    "           ['0',r'$\\frac{\\pi}{2}$','$\\pi$',r'$\\frac{3\\pi}{2}$','$2\\pi$'])\n",
    "plt.ylim(-1.1,1.1,.5)\n",
    "\n",
    "plt.grid(ls =\":\",c ='gray',alpha = .8,lw =1)\n",
    "plt.title('新的标题',\n",
    "          fontdict={'family':'FangSong',\n",
    "                    'size':15,\n",
    "                    'weight':True,})\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}